In silico modelling of multi-electrode arrays for enhancing cardiac drug testing on hiPSC-CM heterogeneous tissues

Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) offer a transformative platform for in vitro and in silico testing of patient-specific drugs, enabling detailed study of cardiac electrophysiology. By integrating standard experimental techniques with extracellular potential measurements from multi-electrode arrays (MEAs), researchers can capture key tissue-level electrophysiological properties, such as action potential dynamics and conduction characteristics. This study presents an innovative computational framework that combines an MEA-based electrophysiological model with phenotype-specific hiPSC-CM ionic models, enabling accurate in silico predictions of drug responses. We tested four drug compounds and ion channel blockers using this model and compared these predictions against experimental MEA data, establishing the model's robustness and reliability. Additionally, we examined how tissue heterogeneity in hiPSC-CMs affects conduction velocity, providing insights into how cellular variations can influence drug efficacy and tissue-level electrical behaviour. Our model was further tested through simulations of Brugada syndrome, successfully replicating pathological electrophysiological patterns observed in adult cardiac tissues. These findings highlight the potential of hiPSC-CM MEA-based in silico modelling for advancing drug screening processes, which have the potential to refine disease-specific therapy development, and improve patient outcomes in complex cardiac conditions. KEY POINTS: Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) offer a transformative platform for in vitro and in silico testing of patient-specific drugs, enabling detailed study of cardiac electrophysiology. Development of an innovative computational framework that combines a multi-electrode array (MEA)-based electrophysiological model with phenotype-specific hiPSC-CM ionic models. Drug testing of four compounds and ion channel blockers using this hiPSC-CM MEA model and comparison against experimental MEA data, establishing the model's robustness and reliability. Study of the effect of tissue heterogeneity in hiPSC-CMs on conduction velocity, providing insights into how cellular variations can influence drug efficacy and tissue-level electrical behaviour. Brugada syndrome simulation through the hiPSC-CM MEA model, successfully replicating pathological electrophysiological patterns observed in adult cardiac tissues.